1. Field of the Invention
The present invention relates to quality control of seismic data processing. Specifically, the present invention involves computerized evaluation of seismic data processing software, and more particularly evaluation of how the data processing software alters the actual content of the data being processed.
2. Description of the Prior Art
Seismic attributes play a key role in seismic data interpretation. Examples of attributes used in seismic data interpretation include amplitude, phase, central frequency, bandwidth, signal-to-noise ratio, crosscorrelation coefficient and the like. Seismic attributes also can provide useful information for seismic-processing quality control, because attributes are sensitive to relative changes that the seismic data undergo during processing. Displays of seismic attributes have been monitored to detect processing-induced changes in the data and thereby catch processing mistakes, such as poor/wrong parameter choices, and software bugs.
So far as is known, trained analysts traditionally attempted this by examining seismic data displays, before and after processing, a technique sometimes referred to as beauty contests. These visual approaches were subjective and interpretive. Real data are noisy and composed of many reflection events, and data displays rarely yielded objective interpretations. Small-to-medium scale details which would be more indicative of data processing changes might not even appear in data displays.
Further, processing parameters selected for use in processing data also could affect the content of the data. Examples of these types of parameters included time shift, deconvolution operator length, migration aperture width, velocity function and the like. Again, so far as is known, these parameters have been selected by visual, subjective comparisons of processing results using various values of a parameter in question. As has been already mentioned, real seismic data are noisy and composed of many events. Small scale details, which would more clearly illustrate ineffective or distorting parameter values, often would not show up in data plots.